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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1969

Solar activity history model

Solar activity model provides information on plages, sunspots, filaments, and flares. The model enables scheduling, which will indicate the time periods when solar experiments can be conducted. Data were collected at various locations throughout the world and recorded on tape for the computer.

Mc Kowen, P.↗
NASA NTRS1980

Lunar highland crustal models based on iron concentrations - Isostasy and center-of-mass displacement

Data is introduced on the iron concentrations of the lunar surface which have been refined by means of convolution corrections to restore the spatial resolution and contrast lost by the omnidirectional spectrometer. This refined iron data is synthesized with other orbital seismic, and lunar sample data to derive highland crustal density and thickness, and isostasy and lunar centers of mass models are examined in light of this new information. A model is developed by which highland crustal density is calculated for each highland region from orbital observations of Fe, Mg and Ti concentrations. The results of this model are presented numerically and graphically for 35 highland and two non-highland regions. Density and thickness results are then applied to two long-standing lunar problems: (1) the nature of highland isostasy, which is shown to be controlled by crustal thickness rather than density, and (2) the separation of the moon's mass and figure centers, which is shown to be due to the crustal thickness difference between the lunar near and far sides.

Haines, E. L.↗
NASA NTRS1983

Gamma-ray spectroscopy - Status and prospects

Contemporary gamma-ray spectroscopy instruments and their results are reviewed. Sensitivities of 10 to the -4th to 10 to the -3rd ph/sq cm-sec have been achieved for steady sources and 10 to the -2nd to 1 ph/sq cm-sec for transient sources. This has led to the detection of gamma-ray lines from more than 40 objects representing 6 classes of astrophysical phenomena. The lines carry model-independent information and are of fundamental importance to theoretical modeling and our understanding of the objects. The objectives and anticipated results of future instruments are discussed. Several instruments in development will have a factor of 10 sensitivity improvement to certain phenomena over contemporary instruments. A factor of 100 improvement in sensitivity will allow the full potential of gamma-ray spectroscopy to be realized. Instrument concepts which would achieve this with both present and advanced techniques are discussed.

Matteson, J. L.↗
NASA NTRS2010

Bird Migration Under Climate Change - A Mechanistic Approach Using Remote Sensing

The broad-scale reductions and shifts that may be expected under climate change in the availability and quality of stopover habitat for long-distance migrants is an area of increasing concern for conservation biologists. Researchers generally have taken two broad approaches to the modeling of migration behaviour to understand the impact of these changes on migratory bird populations. These include models based on causal processes and their response to environmental stimulation, "mechanistic models", or models that primarily are based on observed animal distribution patterns and the correlation of these patterns with environmental variables, i.e. "data driven" models. Investigators have applied the latter technique to forecast changes in migration patterns with changes in the environment, for example, as might be expected under climate change, by forecasting how the underlying environmental data layers upon which the relationships are built will change over time. The learned geostatstical correlations are then applied to the modified data layers.. However, this is problematic. Even if the projections of how the underlying data layers will change are correct, it is not evident that the statistical relationships will remain the same, i.e. that the animal organism may not adapt its' behaviour to the changing conditions. Mechanistic models that explicitly take into account the physical, biological, and behaviour responses of an organism as well as the underlying changes in the landscape offer an alternative to address these shortcomings. The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies enable the application of the mechanistic models to predict how continental bird migration patterns may change in response to environmental change. In earlier work, we simulated the impact of effects of wetland loss and inter-annual variability on the fitness of migratory shorebirds in the central fly ways of North America. We demonstrated the phenotypic plasticity of a migratory population of Pectoral sandpipers consisting of an ensemble of 10,000 individual birds in response to changes in stopover locations using an individual based migration model driven by remotely sensed land surface data, climate data and biological field data. With the advent of new computing capabilities enabled hy recent GPU-GP computing paradigms and commodity hardware, it now is possible to simulate both larger ensemble populations and to incorporate more realistic mechanistic factors into migration models. Here, we take our first steps use these tools to study the impact of long-term drought variability on shorebird survival.

Smith, James A.↗
NASA NTRS2017

Integrated Model of the Eye/Optic Nerve Head Biomechanical Environment

Visual Impairment and Intracranial Pressure (VIIP) syndrome is a concern for long-duration space flight. Previously, it has been suggested that ocular changes observed in VIIP syndrome are related to the cephalad fluid shift that results in altered fluid pressures [1]. We are investigating the impact of changes in intracranial pressure (ICP) using a combination of numerical models, which simulate the effects of various environment conditions, including finite element (FE) models of the posterior eye. The specific interest is to understand how altered pressures due to gravitational changes affect the biomechanical environment of tissues of the posterior eye and optic nerve sheath. METHODS: Additional description of the numerical modeling is provided in the IWS abstract by Nelson et al. In brief, to simulate the effects of a cephalad fluid shift on the cardiovascular and ocular systems, we utilized a lumped-parameter compartment model of these systems. The outputs of this lumped-parameter model then inform boundary conditions (pressures) for a finite element model of the optic nerve head (Figure 1). As an example, we show here a simulation of postural change from supine to 15 degree head-down tilt (HDT), with primary outcomes being the predicted change in strains at the optic nerve head (ONH) region, specifically in the lamina cribrosa (LC), retrolaminar optic nerve, and prelaminar neural tissue (PLNT). The strain field can be decomposed into three orthogonal components, denoted as the first, second and third principal strains. We compare the peak tensile (first principal) and compressive (third principal) strains, since elevated strain alters cell phenotype and induces tissue remodeling. RESULTS AND CONCLUSIONS: Our lumped-parameter model predicted an IOP increase of c. 7 mmHg after 21 minutes of 15 degree HDT, which agreed with previous reports of IOP in HDT [1]. The corresponding FEM simulations predicted a relative increase in the magnitudes of the peak tensile and compressive strains in the lamina cribrosa of 42 and 43, respectively (Fig. 2). The corresponding changes in the optic nerve strains were 17 and 39, while in the PLNT they were 47 and 43. These magnitudes of relative elevations in peak strains may induce a phenotypic response in resident mechano-responsive resident cells [2]. This approach may be expanded to investigate other environmental changes (e.g. parabolic flight). Through our VIIP SCHOLAR project, we will validate and improve these integrated models by measuring patient-specific changes in optic nerve sheath geometry in patients with idiopathic intracranial hypertension before and after lumbar puncture and CSF removal.

biomechanics↗
NASA NTRS2020

Release of the NASA Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) OpenVSP Model

The Open VSP model represents the geometry of PEGASUS as is currently modeled. PEGASUS is a concept vehicle that will not be physically produced. As such, the baseline model is subject to change without notice or requirement that updates are provided external to NASA. The current baseline is derived from the outer mold line (OML) of the ATR 42-500. As such, planform areas for the wing, fuselage, vertical tail, and horizontal tail mimic those published in public ATR 42 literature. NASA Aeronautics Systems Analysis Branch (ASAB) does not contain any proprietary data on the ATR 42, thus the PEGASUS model does not contain any proprietary or sensitive information. Further, model details that are required for an actual aircraft such as airfoils, twist distributions and propeller geometries are unknown at this time, and generic stand-ins are used within the OpenVSP model. The intent is to provide this model to Georgia Tech ASDL to allow the ASDL team to model the impact of the propulsion system at the wingtip’s impact on structural characteristics. The ASDL will be using the model to generate estimated aerodynamic load and structural members for analysis.

PEGASUS↗
DOE OSTI2021

Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution

Recent works exploring deep learning application to dynamical systems modeling have demonstrated that embedding physical priors into neural networks can yield more effective, physically-realistic, and data-efficient models. However, in the absence of complete prior knowledge of a dynamical system's physical characteristics, determining the optimal structure and optimization strategy for these models can be difficult. In this work, we explore methods for discovering neural state space dynamics models for system identification. Starting with a design space of block-oriented state space models and structured linear maps with strong physical priors, we encode these components into a model genome alongside network structure, penalty constraints, and optimization hyperparameters. Demonstrating the overall utility of the design space, we employ an asynchronous genetic search algorithm that alternates between model selection and optimization and obtains accurate physically consistent models of three physical systems: an aerodynamics body, a continuous stirred tank reactor, and a two tank interacting system.

genetic algorithms, neural architecture search, ne↗
DOE OSTI2022

Phase-field simulations to inform nuclear fuel performance modeling

Software tools to simulate nuclear fuel performance at the engineering scale, such as Idaho National Laboratory (INL)’s BISON code, are increasingly relied upon in regulatory and economic decision-making. However, accurate results from these tools depends on the availability of materials parameters that are used as input. In recent years, atomistic and mesoscale simulation methods have emerged as a cost-effective, expedient means to obtain such input parameters. Phase-field simulations using INL’s Marmot application have been used to obtain microstructure-level parameters and to improve material models for fuel performance modeling using BISON. In this talk, recent examples of this process are given, including applications in UO2, U3Si2, and UZr fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Natural Language Processing to Inform Agent-Based Modeling: With Application to Modeling Adoption of Medium-Duty Electric Vehicles

Agent-based socio-technical modeling of medium- and heavy-duty (MDHD) electric vehicle (EV) adoption has the potential to provide analysis, prediction, and gui. This paper describes new applications of text analysis developed through machine learning (ML) to build and understand relevant topics and their saliency in the published discourse on adoption of MDHD EVs. This work contributes to the state of the art in topic mining models by defining a new metric of topic ranking (START) that quantifies the importance of predefined topics within the corpus using weighted results for predefined topics from two topic modeling approaches: Latent Dirichlet Allocation (LDA) and BERTopic. The START metric is then demonstrated in practice to model how academia and industry view the EV adoption process based on the respective texts published by these groups. Results show that academic literature places more emphasis on categories of interests such as norms/attitudes and adopter knowledge, while trade journals tend to emphasize long-term cost more than academia. The two bodies of literature agree on the importance of policy and incentives in MDHD EV adoption. Together these results illustrate the potential to use ML-based text analysis to populate the characteristics of agent-based socio-technical models.

Electric vehicle adoption, fleet electrification, ↗
NASA NTRS2006

Integrated Modeling and Simulation Verification, Validation, and Accreditation Strategy for Exploration Systems Mission Directorate

Models and simulations (M&S) are critical resources in the exploration of space. They support program management, systems engineering, integration, analysis, test, and operations and provide critical information and data supporting key analyses and decisions (technical, cost and schedule). Consequently, there is a clear need to establish a solid understanding of M&S strengths and weaknesses, and the bounds within which they can credibly support decision-making. Their usage requires the implementation of a rigorous approach to verification, validation and accreditation (W&A) and establishment of formal process and practices associated with their application. To ensure decision-making is suitably supported by information (data, models, test beds) from activities (studies, exercises) from M&S applications that are understood and characterized, ESMD is establishing formal, tailored W&A processes and practices. In addition, to ensure the successful application of M&S within ESMD, a formal process for the certification of analysts that use M&S is being implemented. This presentation will highlight NASA's Exploration Systems Mission Directorate (ESMD) management approach for M&S W&A to ensure decision-makers receive timely information on the model's fidelity, credibility, and quality.

Hale, Joseph P.↗
DOE OSTI2022

Semantic Property Graph for Scalable Knowledge Graph Analytics

Graphs are a natural and fundamental representation to describe entities, relationships, activities, and evolution of complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Resource Description Framework (RDF) and Labeled Property Graph (LPG) are two of the most used data models to encode information in a graph. Both models are similar in terms of using basic graph elements such as nodes and edges but differ in terms of the modeling approach, expressibility, serialization, and target applications. RDF is a flexible data exchange model for expressing information about entities but it tends to a have high memory footprint and inefficient storage, which does not make it a natural choice to perform scalable graph analytics. In contrast, LPG has gained traction as a reliable model to perform scalable graph analytic tasks such as sub-graph matching, network alignment, and real-time knowledge graph query. It provides efficient storage, fast traversal, and flexibility to model various real-world domains. At the same time, the LPG lacks the support of a formal knowledge representation such as an ontology to provide automated knowledge inference. We propose Semantic Property Graph (SPG) as a logical projection of reified RDF into the LPG model. SPG continues to use RDF ontology to define the type hierarchy of the projected graph and validate it against a given ontology. We present a framework to convert reified RDF graphs into SPG using two different computing environments. We also present cloud-based graph migration capabilities using Amazon Web Services.

Purohit, Sumit↗
NASA NTRS1977

Binocular device for displaying numerical information in field of view

An apparatus is described for superimposing numerical information on the field of view of binoculars. The invention has application in the flying of radio-controlled model airplanes. Information such as airspeed and angle of attack are sensed on a model airplane and transmitted back to earth where this information is changed into numerical form. Optical means are attached to the binoculars that a pilot is using to track the model air plane for displaying the numerical information in the field of view of the binoculars. The device includes means for focusing the numerical information at infinity whereby the user of the binoculars can see both the field of view and the numerical information without refocusing his eyes.

Fuller, H. V.↗